Containers improve the efficiency in application deployment and thus have been widely
utilised on Cloud and lately in High Performance Computing (HPC) environments …

TensorDash is a hardware-based technique that enables data-parallel MAC units to take
advantage of sparsity in their input operand streams. When used to compose a hardware …

The generative adversarial network (GAN) is usually built from the centralized, independent
identically distributed (iid) training data to generate realistic-like instances. In real-world …

Deep learning has recently become very popular on account of its incredible success in
many complex datadriven applications, including image classification and speech …

Containerisation demonstrates its efficiency in application deployment in Cloud Computing.
Containers can encapsulate complex programs with their dependencies in isolated …

Large-scale training is important to ensure high performance and accuracy of machine-
learning models. At Facebook we use many different models, including computer vision …

The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …

Deep learning (DL) has demonstrated its remarkable success in a wide variety of fields. The
development of a DL model is a time-consuming and resource-intensive procedure. Hence …

Using machine learning for pluvial flood prediction tasks has gained growing attention in the
past years. In particular, data-driven models using artificial neuronal networks show …

Abstract Advances in Deep Learning (DL), Big Data and image processing have facilitated
online disinformation spreading through Deepfakes. This entails severe threats including …